import pandas as pd

import re 

import numpy as np

df1

import matplotlib.pyplot as plt

from matplotlib.pyplot import figure

%matplotlib inline

df1

df1['Imp in per'] =df1['Importance']*100

df1

X2 =df1['NPS score']

Y2 =df1['Imp in per']

x_line =df1['NPS score'].mean()

y_line =df1['Imp in per'].mean()

df1['Imp in per'] =df1['Importance']*100

from matplotlib.pyplot import figure

annotations=[i for i in df1['Categories']]

nps =[i for i in df1['NPS score']]

Importance = [i for i in df1['Importance']]

Importance_in_percent = [i for i in df1['Imp in per']]

annotations=[i for i in df1['Categories']]

nps =[i for i in df1['NPS score']]

Importance = [i for i in df1['Importance']]

figure(figsize=(50, 60), dpi=80)

plt.scatter(X2, Y2,c='magenta',s =500)

plt.title('BHIM Quadrant',fontsize=25)

plt.xlabel('NPS score',fontsize=25)

plt.ylabel('Importnace',fontsize=25)

plt.axhline(y = y_line, color = 'r', linestyle = '-')

plt.axvline(x = x_line, color = 'r', linestyle = '-')

plt.xticks([i for i in df1['NPS score']])

plt.yticks([i for i in df1['Imp in per']])

​

for i, label in enumerate(annotations):

    plt.annotate(label, (X2[i], Y2[i]),fontsize=25)

# for i, label in enumerate(nps):

#     plt.annotate(label, (X2[i], Y2[i]),fontsize=15)

# for i, label in enumerate(Importance):

#     plt.annotate(label, (X2[i], Y2[i]),fontsize=15)

​

annotations=[i for i in df1['Categories']]

nps =[i for i in df1['NPS score']]

Importance = [i for i in df1['Importance']]

figure(figsize=(30, 40), dpi=80)

plt.scatter(X2, Y2,c='magenta',s =500)

plt.title('BHIM Quadrant',fontsize=25)

plt.xlabel('NPS score',fontsize=25)

plt.ylabel('Importnace',fontsize=25)

plt.axhline(y = y_line, color = 'r', linestyle = '-')

plt.axvline(x = x_line, color = 'r', linestyle = '-')

plt.xticks([i for i in df1['NPS score']])

plt.yticks([i for i in df1['Imp in per']])

​

for i, label in enumerate(annotations):

    plt.annotate(label, (X2[i], Y2[i]),fontsize=25)

# for i, label in enumerate(nps):

#     plt.annotate(label, (X2[i], Y2[i]),fontsize=15)

# for i, label in enumerate(Importance):

#     plt.annotate(label, (X2[i], Y2[i]),fontsize=15)

​

# !pip install plotly

import plotly.express as px

df2 =px.data.iris()

df2

df1

# fig = px.scatter(data_frame=df1,x ='NPS score',y='Imp in per',color='Categories',size ='Importance')

fig = px.scatter(data_frame=df1,x ='NPS score',y='Imp in per',text = 'NPS score',color='Categories')

# fig.update_layout(shapes=[

# fig.add_hline(y =x_line)

fig.add_vline(x =x_line)

fig.add_hline(y =y_line)

​

#     dict(

#       type= 'line',

#       yref= y_line,

#       xref= x_line

#     )

# ])

​

fig.show()

​

​

​

fig = px.scatter(data_frame=df1,x ='NPS score',y='Imp in per',color='Categories',size ='Imp in per',text = 'NPS score')

# fig = px.scatter(data_frame=df1,x ='NPS score',y='Imp in per',color='Categories')

# fig.update_layout(shapes=[

# fig.add_hline(y =x_line)

fig.add_vline(x =x_line)

fig.add_hline(y =y_line)

​

#     dict(

#       type= 'line',

#       yref= y_line,

#       xref= x_line

#     )

# ])

​

fig.show()

​

​